Comparative Effectiveness of Adalimumab vs Tofacitinib in Patients With Rheumatoid Arthritis in Australia

Abstract

Importance: There is a need for observational studies to supplement evidence from clinical trials, and the target trial emulation (TTE) framework can help avoid biases that can be introduced when treatments are compared crudely using observational data by applying design principles for randomized clinical trials. Adalimumab (ADA) and tofacitinib (TOF) were shown to be equivalent in patients with rheumatoid arthritis (RA) in a randomized clinical trial, but to our knowledge, these drugs have not been compared head-to-head using routinely collected clinical data and the TTE framework.

Objective: To emulate a randomized clinical trial comparing ADA vs TOF in patients with RA who were new users of a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD).

Design, setting, and participants: This comparative effectiveness study emulating a randomized clinical trial of ADA vs TOF included Australian adults aged 18 years or older with RA in the Optimising Patient Outcomes in Australian Rheumatology (OPAL) data set. Patients were included if they initiated ADA or TOF between October 1, 2015, and April 1, 2021; were new b/tsDMARD users; and had at least 1 component of the disease activity score in 28 joints using C-reactive protein (DAS28-CRP) recorded at baseline or during follow-up.

Intervention: Treatment with either ADA (40 mg every 14 days) or TOF (10 mg daily).

Main outcomes and measures: The main outcome was the estimated average treatment effect, defined as the difference in mean DAS28-CRP among patients receiving TOF compared with those receiving ADA at 3 and 9 months after initiating treatment. Missing DAS28-CRP data were multiply imputed. Stable balancing weights were used to account for nonrandomized treatment assignment.

Results: A total of 842 patients were identified, including 569 treated with ADA (387 [68.0%] female; median age, 56 years [IQR, 47-66 years]) and 273 treated with TOF (201 [73.6%] female; median age, 59 years [IQR, 51-68 years]). After applying stable balancing weights, mean DAS28-CRP in the ADA group was 5.3 (95% CI, 5.2-5.4) at baseline, 2.6 (95% CI, 2.5-2.7) at 3 months, and 2.3 (95% CI, 2.2-2.4) at 9 months; in the TOF group, it was 5.3 (95% CI, 5.2-5.4) at baseline, 2.4 (95% CI, 2.2-2.5) at 3 months, and 2.3 (95% CI, 2.1-2.4) at 9 months. The estimated average treatment effect was -0.2 (95% CI, -0.4 to -0.03; P = .02) at 3 months and -0.03 (95% CI, -0.2 to 0.1; P = .60) at 9 months.

Conclusions and relevance: In this study, there was a modest but statistically significant reduction in DAS28-CRP at 3 months for patients receiving TOF compared with those receiving ADA and no difference between treatment groups at 9 months. Three months of treatment with either drug led to clinically relevant average reductions in mean DAS28-CRP, consistent with remission.

Figure 1.. Multistep Analytical Procedure Developed to Estimate the Average Treatment Effect (ATE) of Tofacitinib (TOF) Compared With Adalimumab (ADA)

Random forest multiple imputation (RF-MI) was used to impute plausible values for missing data in the original electronic medical record (EMR) data set. Stable balancing weights (SBWs) were used to balance the baseline characteristics of the ADA and TOF treatment groups. Gray squares in the grid that represents EMR indicate complete data items and white squares, missing data items. In the complete data sets generated by RF-MI, colored squares represent the imputed values. The different colors used for the same data item in different data sets indicate that imputed values were slightly different in each data set. The covariate balance plots indicate that after SBWs were applied, the mean standardized difference in baseline characteristics between the treatment groups was close to 0 compared with before weighting. The ATE was then calculated separately in each imputed data set before pooling to generate a final estimate.

Figure 2.. Flow Diagram of Inclusion and Exclusion of Patients with Rheumatoid Arthritis (RA) in the Optimising Patient Outcomes in Australian Rheumatology Data Set

Stable balancing weights were used to make each treatment group balanced with each other and the 842 total eligible patients. ADA indicates adalimumab; TOF, tofacitinib. ^aMultiple imputation was applied to these patients.

Figure 3.. Standardized Mean Difference in Baseline Characteristics of Adalimumab (ADA) and Tofacitinib (TOF) Treatment Groups Before and After Weighting

Error bars for disease activity score in 28 joints using C-reactive protein (DAS28-CRP) represent the minimum and maximum standardized mean difference values across 10 imputed data sets. The standardized mean difference is the difference between treatment groups in the mean for each covariate divided by its SD for the entire sample. The vertical dashed black lines indicate standardized mean differences of −0.03 and 0.03. ACT indicates Australian Capital Territory; NSW, New South Wales; QLD, Queensland and Western Australia; and TAS, Tasmania.

Figure 4.. Estimated Average Treatment Effect (ATE) for Tofacitinib (TOF) Compared With Adalimumab (ADA) at 3 and 9 Months

Squares represent ATEs, with horizontal lines representing 95% CIs based on bootstrap distributions of the estimates.